Overview

Dataset statistics

Number of variables23
Number of observations1964
Missing cells98
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory307.1 KiB
Average record size in memory160.1 B

Variable types

CAT12
NUM7
BOOL3
URL1

Warnings

timezone has constant value "1964" Constant
name has a high cardinality: 911 distinct values High cardinality
date has a high cardinality: 595 distinct values High cardinality
time has a high cardinality: 1916 distinct values High cardinality
p1 has a high cardinality: 373 distinct values High cardinality
p2 has a high cardinality: 396 distinct values High cardinality
p3 has a high cardinality: 403 distinct values High cardinality
fav_count is highly correlated with retweet_countHigh correlation
retweet_count is highly correlated with fav_countHigh correlation
name has 98 (5.0%) missing values Missing
rating_numerator is highly skewed (γ1 = 39.23799602) Skewed
time is uniformly distributed Uniform
tweet_id has unique values Unique
text has unique values Unique
img_url has unique values Unique

Reproduction

Analysis started2020-12-14 04:30:55.390777
Analysis finished2020-12-14 04:31:12.724084
Duration17.33 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

tweet_id
Categorical

UNIQUE

Distinct1964
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
672622327801233409
 
1
747512671126323200
 
1
674053186244734976
 
1
743609206067040256
 
1
730924654643314689
 
1
Other values (1959)
1959 
ValueCountFrequency (%) 
67262232780123340910.1%
 
74751267112632320010.1%
 
67405318624473497610.1%
 
74360920606704025610.1%
 
73092465464331468910.1%
 
80075157735512883210.1%
 
83493163376988979710.1%
 
75217315293180723210.1%
 
75113287610468761710.1%
 
81098465241242419210.1%
 
Other values (1954)195499.5%
 
2020-12-14T15:31:12.812845image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1964 ?
Unique (%)100.0%
2020-12-14T15:31:12.954510image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length18
Median length18
Mean length18
Min length18

source_app
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
Twitter for iPhone
1926 
Twitter Web Client
 
28
TweetDeck
 
10
ValueCountFrequency (%) 
Twitter for iPhone192698.1%
 
Twitter Web Client281.4%
 
TweetDeck100.5%
 
2020-12-14T15:31:13.083155image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-14T15:31:13.177869image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:13.281626image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length18
Median length18
Mean length17.95417515
Min length9

text
Categorical

UNIQUE

Distinct1964
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
This is Bo. He was a very good First Doggo. 14/10 would be an absolute honor to pet https://t.co/AdPKrI8BZ1
 
1
Meet Chester. He just ate a lot and now he can't move. 10/10 that's going to be me in about 17 hours https://t.co/63jh1tYZa5
 
1
This is Severus. He's here to fix your cable. Looks like he succeeded. Even offered to pupgrade your plan. 13/10 h*ckin helpful https://t.co/aX4brLLpWZ
 
1
This is Ruby. She just turned on the news. Officially terrified. 11/10 deep breaths Ruby https://t.co/y5KarNXWXt
 
1
Vibrant dog here. Fabulous tail. Only 2 legs tho. Has wings but can barely fly (lame). Rather elusive. 5/10 okay pup https://t.co/cixC0M3P1e
 
1
Other values (1959)
1959 
ValueCountFrequency (%) 
This is Bo. He was a very good First Doggo. 14/10 would be an absolute honor to pet https://t.co/AdPKrI8BZ110.1%
 
Meet Chester. He just ate a lot and now he can't move. 10/10 that's going to be me in about 17 hours https://t.co/63jh1tYZa510.1%
 
This is Severus. He's here to fix your cable. Looks like he succeeded. Even offered to pupgrade your plan. 13/10 h*ckin helpful https://t.co/aX4brLLpWZ10.1%
 
This is Ruby. She just turned on the news. Officially terrified. 11/10 deep breaths Ruby https://t.co/y5KarNXWXt10.1%
 
Vibrant dog here. Fabulous tail. Only 2 legs tho. Has wings but can barely fly (lame). Rather elusive. 5/10 okay pup https://t.co/cixC0M3P1e10.1%
 
This is Lacy. She's tipping her hat to you. Daydreams of her life back on the frontier. 11/10 would pet so well https://t.co/fG5Pk3Et1I10.1%
 
We only rate dogs. Please don't send in other things like this very good Christmas tree. Thank you... 13/10 https://t.co/rvSANEsQZJ10.1%
 
This is Billy. He sensed a squirrel. 8/10 damn it Billy https://t.co/Yu0K98VZ9A10.1%
 
I have no words. Just a magnificent pup. 12/10 https://t.co/viwWHZgX8j10.1%
 
This is Brandi and Harley. They are practicing their caroling for later. Both 12/10 festive af https://t.co/AbBDuGZUpp10.1%
 
Other values (1954)195499.5%
 
2020-12-14T15:31:13.422249image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1964 ?
Unique (%)100.0%
2020-12-14T15:31:13.583817image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length167
Median length132
Mean length122.5096741
Min length36

rating_numerator
Real number (ℝ≥0)

SKEWED

Distinct33
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.17605906
Minimum0
Maximum1776
Zeros1
Zeros (%)0.1%
Memory size15.3 KiB
2020-12-14T15:31:13.795583image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6
Q110
median11
Q312
95-th percentile13
Maximum1776
Range1776
Interquartile range (IQR)2

Descriptive statistics

Standard deviation41.67975521
Coefficient of variation (CV)3.423090755
Kurtosis1640.906289
Mean12.17605906
Median Absolute Deviation (MAD)1
Skewness39.23799602
Sum23913.78
Variance1737.201995
MonotocityNot monotonic
2020-12-14T15:31:13.929261image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%) 
1244422.6%
 
1041621.2%
 
1139320.0%
 
1324912.7%
 
91517.7%
 
8954.8%
 
7522.6%
 
14331.7%
 
5321.6%
 
6321.6%
 
Other values (23)673.4%
 
ValueCountFrequency (%) 
010.1%
 
140.2%
 
290.5%
 
3191.0%
 
4160.8%
 
ValueCountFrequency (%) 
177610.1%
 
42010.1%
 
20410.1%
 
16510.1%
 
14410.1%
 

rating_denominator
Real number (ℝ≥0)

Distinct12
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.48472505
Minimum10
Maximum170
Zeros0
Zeros (%)0.0%
Memory size7.7 KiB
2020-12-14T15:31:14.076865image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile10
Q110
median10
Q310
95-th percentile10
Maximum170
Range160
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.862321979
Coefficient of variation (CV)0.6545066223
Kurtosis313.9517317
Mean10.48472505
Median Absolute Deviation (MAD)0
Skewness16.83789194
Sum20592
Variance47.09146294
MonotocityNot monotonic
2020-12-14T15:31:14.208478image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%) 
10194999.2%
 
5030.2%
 
8020.1%
 
1120.1%
 
17010.1%
 
15010.1%
 
12010.1%
 
11010.1%
 
9010.1%
 
7010.1%
 
Other values (2)20.1%
 
ValueCountFrequency (%) 
10194999.2%
 
1120.1%
 
2010.1%
 
4010.1%
 
5030.2%
 
ValueCountFrequency (%) 
17010.1%
 
15010.1%
 
12010.1%
 
11010.1%
 
9010.1%
 

name
Categorical

HIGH CARDINALITY
MISSING

Distinct911
Distinct (%)48.8%
Missing98
Missing (%)5.0%
Memory size15.3 KiB
None
524 
Oliver
 
10
Cooper
 
10
Charlie
 
10
Lucy
 
9
Other values (906)
1303 
ValueCountFrequency (%) 
None52426.7%
 
Oliver100.5%
 
Cooper100.5%
 
Charlie100.5%
 
Lucy90.5%
 
Tucker90.5%
 
Penny90.5%
 
Sadie80.4%
 
Winston80.4%
 
Daisy70.4%
 
Other values (901)126264.3%
 
(Missing)985.0%
 
2020-12-14T15:31:14.438863image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique690 ?
Unique (%)37.0%
2020-12-14T15:31:14.613394image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length14
Median length4
Mean length4.928207739
Min length1

date
Categorical

HIGH CARDINALITY

Distinct595
Distinct (%)30.3%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
2015-11-28
 
26
2015-11-29
 
26
2015-11-16
 
25
2015-11-19
 
23
2015-12-01
 
22
Other values (590)
1842 
ValueCountFrequency (%) 
2015-11-28261.3%
 
2015-11-29261.3%
 
2015-11-16251.3%
 
2015-11-19231.2%
 
2015-12-01221.1%
 
2015-11-25201.0%
 
2015-11-22201.0%
 
2015-12-07201.0%
 
2015-11-23201.0%
 
2015-11-20201.0%
 
Other values (585)174288.7%
 
2020-12-14T15:31:14.811864image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique168 ?
Unique (%)8.6%
2020-12-14T15:31:14.974463image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length10
Mean length10
Min length10

time
Categorical

HIGH CARDINALITY
UNIFORM

Distinct1916
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
01:00:05
 
3
00:08:17
 
3
03:56:12
 
2
16:00:07
 
2
16:10:29
 
2
Other values (1911)
1952 
ValueCountFrequency (%) 
01:00:0530.2%
 
00:08:1730.2%
 
03:56:1220.1%
 
16:00:0720.1%
 
16:10:2920.1%
 
18:27:3220.1%
 
00:53:2720.1%
 
23:33:5820.1%
 
00:38:5220.1%
 
16:53:3720.1%
 
Other values (1906)194298.9%
 
2020-12-14T15:31:15.212793image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1870 ?
Unique (%)95.2%
2020-12-14T15:31:15.463122image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length8
Median length8
Mean length8
Min length8

timezone
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
+00:00
1964 
ValueCountFrequency (%) 
+00:001964100.0%
 
2020-12-14T15:31:15.681540image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-14T15:31:15.786285image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:15.891011image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length6
Mean length6
Min length6

dog_type
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
doggo
1714 
pupper
220 
puppo
 
27
floofer
 
3
ValueCountFrequency (%) 
doggo171487.3%
 
pupper22011.2%
 
puppo271.4%
 
floofer30.2%
 
2020-12-14T15:31:16.068537image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-14T15:31:16.168273image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:16.306867image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length5
Mean length5.115071283
Min length5

retweet_count
Real number (ℝ≥0)

HIGH CORRELATION

Distinct1796
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8131.968941
Minimum69
Maximum152335
Zeros0
Zeros (%)0.0%
Memory size15.3 KiB
2020-12-14T15:31:16.467438image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum69
5-th percentile380.2
Q11744
median3670
Q310153.75
95-th percentile28182.3
Maximum152335
Range152266
Interquartile range (IQR)8409.75

Descriptive statistics

Standard deviation11960.85694
Coefficient of variation (CV)1.470843904
Kurtosis32.34598187
Mean8131.968941
Median Absolute Deviation (MAD)2774.5
Skewness4.460894039
Sum15971187
Variance143062098.8
MonotocityNot monotonic
2020-12-14T15:31:16.609058image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
35540.2%
 
28530.2%
 
301330.2%
 
271630.2%
 
40930.2%
 
209630.2%
 
237630.2%
 
70530.2%
 
275930.2%
 
978530.2%
 
Other values (1786)193398.4%
 
ValueCountFrequency (%) 
6910.1%
 
9310.1%
 
9410.1%
 
9610.1%
 
9810.1%
 
ValueCountFrequency (%) 
15233510.1%
 
12996510.1%
 
11762210.1%
 
11383210.1%
 
11261110.1%
 

fav_count
Real number (ℝ≥0)

HIGH CORRELATION

Distinct1543
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2399.067719
Minimum11
Maximum75413
Zeros0
Zeros (%)0.0%
Memory size15.3 KiB
2020-12-14T15:31:16.776645image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile121
Q1534
median1161
Q32740
95-th percentile7720.2
Maximum75413
Range75402
Interquartile range (IQR)2206

Descriptive statistics

Standard deviation4287.118887
Coefficient of variation (CV)1.786993695
Kurtosis82.15706639
Mean2399.067719
Median Absolute Deviation (MAD)798.5
Skewness7.25348446
Sum4711769
Variance18379388.35
MonotocityNot monotonic
2020-12-14T15:31:16.929246image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
5150.3%
 
54640.2%
 
58940.2%
 
8940.2%
 
44540.2%
 
20240.2%
 
8140.2%
 
54940.2%
 
112240.2%
 
94140.2%
 
Other values (1533)192397.9%
 
ValueCountFrequency (%) 
1110.1%
 
1810.1%
 
2910.1%
 
3110.1%
 
3210.1%
 
ValueCountFrequency (%) 
7541310.1%
 
5614610.1%
 
5498710.1%
 
4246710.1%
 
3954810.1%
 

img_url
URL

UNIQUE

Distinct1964
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
https://pbs.twimg.com/media/CzBD7MWVIAA5ptx.jpg
 
1
https://pbs.twimg.com/media/CysBn-lWIAAoRx1.jpg
 
1
https://pbs.twimg.com/media/CU6xVkbWsAAeHeU.jpg
 
1
https://pbs.twimg.com/media/CzG425nWgAAnP7P.jpg
 
1
https://pbs.twimg.com/media/CwxfrguUUAA1cbl.jpg
 
1
Other values (1959)
1959 
ValueCountFrequency (%) 
https://pbs.twimg.com/media/CzBD7MWVIAA5ptx.jpg10.1%
 
https://pbs.twimg.com/media/CysBn-lWIAAoRx1.jpg10.1%
 
https://pbs.twimg.com/media/CU6xVkbWsAAeHeU.jpg10.1%
 
https://pbs.twimg.com/media/CzG425nWgAAnP7P.jpg10.1%
 
https://pbs.twimg.com/media/CwxfrguUUAA1cbl.jpg10.1%
 
https://pbs.twimg.com/media/CUmGu7-UcAA0r3O.jpg10.1%
 
https://pbs.twimg.com/media/CWJQ4UmWoAIJ29t.jpg10.1%
 
https://pbs.twimg.com/media/CV6aMToXIAA7kH4.jpg10.1%
 
https://pbs.twimg.com/media/C8GPrNDW4AAkLde.jpg10.1%
 
https://pbs.twimg.com/media/CUES51dXIAEahyG.jpg10.1%
 
Other values (1954)195499.5%
 
ValueCountFrequency (%) 
https1964100.0%
 
ValueCountFrequency (%) 
pbs.twimg.com1964100.0%
 
ValueCountFrequency (%) 
/media/CWOt07EUsAAnOYW.jpg10.1%
 
/media/CxZaqh_WQAA7lY3.jpg10.1%
 
/media/CUJPNjOWsAAZRqP.jpg10.1%
 
/media/CnH87L6XYAAF7I_.jpg10.1%
 
/media/CyeTku-XcAALkBd.jpg10.1%
 
/media/CcPNS4yW8AAd-Et.jpg10.1%
 
/media/CUyZ6mVW4AI8YWZ.jpg10.1%
 
/media/CfNUNetW8AAekHx.jpg10.1%
 
/media/Ca3i7CzXIAMLhg8.jpg10.1%
 
/media/CUibq3uVAAAup_O.jpg10.1%
 
Other values (1954)195499.5%
 
ValueCountFrequency (%) 
1964100.0%
 
ValueCountFrequency (%) 
1964100.0%
 

conf_tweet_img
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
1
1686 
2
189 
3
 
59
4
 
30
ValueCountFrequency (%) 
1168685.8%
 
21899.6%
 
3593.0%
 
4301.5%
 
2020-12-14T15:31:17.116733image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-14T15:31:17.219461image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:17.353068image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

p1
Categorical

HIGH CARDINALITY

Distinct373
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
golden_retriever
 
137
labrador_retriever
 
92
pembroke
 
88
chihuahua
 
78
pug
 
54
Other values (368)
1515 
ValueCountFrequency (%) 
golden_retriever1377.0%
 
labrador_retriever924.7%
 
pembroke884.5%
 
chihuahua784.0%
 
pug542.7%
 
chow412.1%
 
samoyed392.0%
 
pomeranian381.9%
 
toy_poodle361.8%
 
malamute291.5%
 
Other values (363)133267.8%
 
2020-12-14T15:31:17.515666image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique175 ?
Unique (%)8.9%
2020-12-14T15:31:17.682188image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length30
Median length10
Mean length11.35081466
Min length2

p1_conf
Real number (ℝ≥0)

Distinct1961
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5939284387
Minimum0.0443334
Maximum1
Zeros0
Zeros (%)0.0%
Memory size15.3 KiB
2020-12-14T15:31:17.821846image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.0443334
5-th percentile0.16678155
Q10.36277525
median0.587357
Q30.8470625
95-th percentile0.9902437
Maximum1
Range0.9556666
Interquartile range (IQR)0.48428725

Descriptive statistics

Standard deviation0.2721339786
Coefficient of variation (CV)0.4581932113
Kurtosis-1.259241041
Mean0.5939284387
Median Absolute Deviation (MAD)0.241926
Skewness-0.06334829058
Sum1166.475454
Variance0.0740569023
MonotocityNot monotonic
2020-12-14T15:31:17.976435image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.78608920.1%
 
0.24060220.1%
 
0.87323320.1%
 
0.44533410.1%
 
0.24059110.1%
 
0.78716410.1%
 
0.70018210.1%
 
0.89731210.1%
 
0.76999910.1%
 
0.19421110.1%
 
Other values (1951)195199.3%
 
ValueCountFrequency (%) 
0.044333410.1%
 
0.055379410.1%
 
0.059032610.1%
 
0.063151810.1%
 
0.07007610.1%
 
ValueCountFrequency (%) 
110.1%
 
0.99998410.1%
 
0.99996210.1%
 
0.99995610.1%
 
0.99995310.1%
 

p1_dog
Boolean

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
True
1456 
False
508 
ValueCountFrequency (%) 
True145674.1%
 
False50825.9%
 
2020-12-14T15:31:18.082151image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

p2
Categorical

HIGH CARDINALITY

Distinct396
Distinct (%)20.2%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
labrador_retriever
 
95
golden_retriever
 
81
cardigan
 
73
chihuahua
 
43
chesapeake_bay_retriever
 
40
Other values (391)
1632 
ValueCountFrequency (%) 
labrador_retriever954.8%
 
golden_retriever814.1%
 
cardigan733.7%
 
chihuahua432.2%
 
chesapeake_bay_retriever402.0%
 
french_bulldog392.0%
 
pomeranian381.9%
 
toy_poodle361.8%
 
siberian_husky331.7%
 
cocker_spaniel321.6%
 
Other values (386)145474.0%
 
2020-12-14T15:31:18.196844image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique193 ?
Unique (%)9.8%
2020-12-14T15:31:18.343419image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length30
Median length10
Mean length11.81313646
Min length2

p2_conf
Real number (ℝ≥0)

Distinct1959
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1346393172
Minimum1.0113e-08
Maximum0.488014
Zeros0
Zeros (%)0.0%
Memory size15.3 KiB
2020-12-14T15:31:18.877027image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1.0113e-08
5-th percentile0.0043655175
Q10.053527225
median0.1173995
Q30.19556175
95-th percentile0.32585675
Maximum0.488014
Range0.4880139899
Interquartile range (IQR)0.142034525

Descriptive statistics

Standard deviation0.1009430244
Coefficient of variation (CV)0.7497291764
Kurtosis0.1103241388
Mean0.1346393172
Median Absolute Deviation (MAD)0.0697138
Skewness0.7674484146
Sum264.4316191
Variance0.01018949418
MonotocityNot monotonic
2020-12-14T15:31:19.028621image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.15312620.1%
 
0.10838220.1%
 
0.34529820.1%
 
0.069361720.1%
 
0.15048720.1%
 
0.15967210.1%
 
0.020758110.1%
 
0.08873910.1%
 
0.11700310.1%
 
0.030666410.1%
 
Other values (1949)194999.2%
 
ValueCountFrequency (%) 
1.0113e-0810.1%
 
1.00288e-0510.1%
 
1.44895e-0510.1%
 
1.76343e-0510.1%
 
2.33591e-0510.1%
 
ValueCountFrequency (%) 
0.48801410.1%
 
0.46767810.1%
 
0.46481610.1%
 
0.46056510.1%
 
0.45493710.1%
 

p2_dog
Boolean

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
True
1473 
False
491 
ValueCountFrequency (%) 
True147375.0%
 
False49125.0%
 
2020-12-14T15:31:19.132309image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

p3
Categorical

HIGH CARDINALITY

Distinct403
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
labrador_retriever
 
76
chihuahua
 
57
golden_retriever
 
45
eskimo_dog
 
36
kelpie
 
33
Other values (398)
1717 
ValueCountFrequency (%) 
labrador_retriever763.9%
 
chihuahua572.9%
 
golden_retriever452.3%
 
eskimo_dog361.8%
 
kelpie331.7%
 
kuvasz311.6%
 
chow301.5%
 
staffordshire_bullterrier301.5%
 
toy_poodle291.5%
 
beagle281.4%
 
Other values (393)156979.9%
 
2020-12-14T15:31:19.249030image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique182 ?
Unique (%)9.3%
2020-12-14T15:31:19.391616image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length30
Median length10
Mean length11.47046843
Min length2

p3_conf
Real number (ℝ≥0)

Distinct1962
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.06028936073
Minimum1.74017e-10
Maximum0.273419
Zeros0
Zeros (%)0.0%
Memory size15.3 KiB
2020-12-14T15:31:19.513290image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1.74017e-10
5-th percentile0.00086912295
Q10.016197075
median0.0494792
Q30.091622775
95-th percentile0.15712265
Maximum0.273419
Range0.2734189998
Interquartile range (IQR)0.0754257

Descriptive statistics

Standard deviation0.05096696569
Coefficient of variation (CV)0.8453724683
Kurtosis0.4520632132
Mean0.06028936073
Median Absolute Deviation (MAD)0.0368075
Skewness0.8946179434
Sum118.4083045
Variance0.002597631592
MonotocityNot monotonic
2020-12-14T15:31:19.643978image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.1571320.1%
 
0.1014220.1%
 
0.063703110.1%
 
0.031217910.1%
 
0.025874310.1%
 
0.025456310.1%
 
0.20939310.1%
 
0.065813410.1%
 
0.11390310.1%
 
0.094353310.1%
 
Other values (1952)195299.4%
 
ValueCountFrequency (%) 
1.74017e-1010.1%
 
2.1609e-0710.1%
 
5.59504e-0710.1%
 
8.83283e-0710.1%
 
1.43447e-0610.1%
 
ValueCountFrequency (%) 
0.27341910.1%
 
0.27104210.1%
 
0.27067310.1%
 
0.25518210.1%
 
0.24761910.1%
 

p3_dog
Boolean

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
True
1424 
False
540 
ValueCountFrequency (%) 
True142472.5%
 
False54027.5%
 
2020-12-14T15:31:19.743674image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Interactions

2020-12-14T15:31:00.631961image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:00.868330image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:01.058822image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:01.298180image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:01.478697image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:01.632286image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:01.770948image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:01.911541image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:02.069118image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:02.332414image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:02.673152image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:02.901541image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:03.121959image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:03.317436image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:03.549838image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:03.754366image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:03.941865image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:04.249058image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:04.581111image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:04.858135image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:05.190643image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:05.510791image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:05.863897image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:06.137806image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:06.359033image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:06.621335image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:06.916539image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:07.519926image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:07.714410image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:07.918859image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:08.192474image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:08.388943image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:08.550511image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:08.741009image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:09.045194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:09.217494image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:09.373050image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:09.529629image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:09.689200image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:09.849771image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:09.996408image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:10.152960image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:10.303557image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:10.456182image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:10.599765image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:10.759342image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:10.914958image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:11.055546image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:11.202189image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2020-12-14T15:31:19.834435image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-12-14T15:31:20.115679image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-12-14T15:31:20.414879image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-12-14T15:31:20.722057image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2020-12-14T15:31:20.965455image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2020-12-14T15:31:11.504346image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:12.253376image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-14T15:31:12.494697image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Sample

First rows

tweet_idsource_apptextrating_numeratorrating_denominatornamedatetimetimezonedog_typeretweet_countfav_countimg_urlconf_tweet_imgp1p1_confp1_dogp2p2_confp2_dogp3p3_confp3_dog
0892420643555336193Twitter for iPhoneThis is Phineas. He's a mystical boy. Only ever appears in the hole of a donut. 13/10 https://t.co/MgUWQ76dJU13.010Phineas2017-08-0116:23:56+00:00doggo353577467https://pbs.twimg.com/media/DGKD1-bXoAAIAUK.jpg1orange0.097049Falsebagel0.085851Falsebanana0.076110False
1892177421306343426Twitter for iPhoneThis is Tilly. She's just checking pup on you. Hopes you're doing ok. If not, she's available for pats, snugs, boops, the whole bit. 13/10 https://t.co/0Xxu71qeIV13.010Tilly2017-08-0100:17:27+00:00doggo306065544https://pbs.twimg.com/media/DGGmoV4XsAAUL6n.jpg1chihuahua0.323581Truepekinese0.090647Truepapillon0.068957True
2891815181378084864Twitter for iPhoneThis is Archie. He is a rare Norwegian Pouncing Corgo. Lives in the tall grass. You never know when one may strike. 12/10 https://t.co/wUnZnhtVJB12.010Archie2017-07-3100:18:03+00:00doggo230293670https://pbs.twimg.com/media/DGBdLU1WsAANxJ9.jpg1chihuahua0.716012Truemalamute0.078253Truekelpie0.031379True
3891689557279858688Twitter for iPhoneThis is Darla. She commenced a snooze mid meal. 13/10 happens to the best of us https://t.co/tD36da7qLQ13.010Darla2017-07-3015:58:51+00:00doggo386297634https://pbs.twimg.com/media/DF_q7IAWsAEuuN8.jpg1paper_towel0.170278Falselabrador_retriever0.168086Truespatula0.040836False
4891327558926688256Twitter for iPhoneThis is Franklin. He would like you to stop calling him "cute." He is a very fierce shark and should be respected as such. 12/10 #BarkWeek https://t.co/AtUZn91f7f12.010Franklin2017-07-2916:00:24+00:00doggo368968240https://pbs.twimg.com/media/DF6hr6BUMAAzZgT.jpg2basset0.555712Trueenglish_springer0.225770Truegerman_short-haired_pointer0.175219True
5891087950875897856Twitter for iPhoneHere we have a majestic great white breaching off South Africa's coast. Absolutely h*ckin breathtaking. 13/10 (IG: tucker_marlo) #BarkWeek https://t.co/kQ04fDDRmh13.010None2017-07-2900:08:17+00:00doggo186082755https://pbs.twimg.com/media/DF3HwyEWsAABqE6.jpg1chesapeake_bay_retriever0.425595Trueirish_terrier0.116317Trueindian_elephant0.076902False
6890971913173991426Twitter for iPhoneMeet Jax. He enjoys ice cream so much he gets nervous around it. 13/10 help Jax enjoy more things by clicking below\n\nhttps://t.co/Zr4hWfAs1H https://t.co/tVJBRMnhxl13.010Jax2017-07-2816:27:12+00:00doggo108071791https://pbs.twimg.com/media/DF1eOmZXUAALUcq.jpg1appenzeller0.341703Trueborder_collie0.199287Trueice_lolly0.193548False
7890729181411237888Twitter for iPhoneWhen you watch your owner call another dog a good boy but then they turn back to you and say you're a great boy. 13/10 https://t.co/v0nONBcwxq13.010None2017-07-2800:22:40+00:00doggo5954516705https://pbs.twimg.com/media/DFyBahAVwAAhUTd.jpg2pomeranian0.566142Trueeskimo_dog0.178406Truepembroke0.076507True
8890609185150312448Twitter for iPhoneThis is Zoey. She doesn't want to be one of the scary sharks. Just wants to be a snuggly pettable boatpet. 13/10 #BarkWeek https://t.co/9TwLuAGH0b13.010Zoey2017-07-2716:25:51+00:00doggo256263813https://pbs.twimg.com/media/DFwUU__XcAEpyXI.jpg1irish_terrier0.487574Trueirish_setter0.193054Truechesapeake_bay_retriever0.118184True
9890240255349198849Twitter for iPhoneThis is Cassie. She is a college pup. Studying international doggo communication and stick theory. 14/10 so elegant much sophisticate https://t.co/t1bfwz5S2A14.010Cassie2017-07-2615:59:51+00:00doggo292306479https://pbs.twimg.com/media/DFrEyVuW0AAO3t9.jpg1pembroke0.511319Truecardigan0.451038Truechihuahua0.029248True

Last rows

tweet_idsource_apptextrating_numeratorrating_denominatornamedatetimetimezonedog_typeretweet_countfav_countimg_urlconf_tweet_imgp1p1_confp1_dogp2p2_confp2_dogp3p3_confp3_dog
1954666058600524156928Twitter for iPhoneHere is the Rand Paul of retrievers folks! He's probably good at poker. Can drink beer (lol rad). 8/10 good dog https://t.co/pYAJkAe76p8.010None2015-11-1601:01:59+00:00doggo10351https://pbs.twimg.com/media/CT5Qw94XAAA_2dP.jpg1miniature_poodle0.201493Truekomondor0.192305Truesoft-coated_wheaten_terrier0.082086True
1955666057090499244032Twitter for iPhoneMy oh my. This is a rare blond Canadian terrier on wheels. Only $8.98. Rather docile. 9/10 very rare https://t.co/yWBqbrzy8O9.010None2015-11-1600:55:59+00:00doggo263120https://pbs.twimg.com/media/CT5PY90WoAAQGLo.jpg1shopping_cart0.962465Falseshopping_basket0.014594Falsegolden_retriever0.007959True
1956666055525042405380Twitter for iPhoneHere is a Siberian heavily armored polar bear mix. Strong owner. 10/10 I would do unspeakable things to pet this dog https://t.co/rdivxLiqEt10.010None2015-11-1600:49:46+00:00doggo403214https://pbs.twimg.com/media/CT5N9tpXIAAifs1.jpg1chow0.692517Truetibetan_mastiff0.058279Truefur_coat0.054449False
1957666051853826850816Twitter for iPhoneThis is an odd dog. Hard on the outside but loving on the inside. Petting still fun. Doesn't play catch well. 2/10 https://t.co/v5A4vzSDdc2.010None2015-11-1600:35:11+00:00doggo1098752https://pbs.twimg.com/media/CT5KoJ1WoAAJash.jpg1box_turtle0.933012Falsemud_turtle0.045885Falseterrapin0.017885False
1958666050758794694657Twitter for iPhoneThis is a truly beautiful English Wilson Staff retriever. Has a nice phone. Privileged. 10/10 would trade lives with https://t.co/fvIbQfHjIe10.010None2015-11-1600:30:50+00:00doggo12151https://pbs.twimg.com/media/CT5Jof1WUAEuVxN.jpg1bernese_mountain_dog0.651137Trueenglish_springer0.263788Truegreater_swiss_mountain_dog0.016199True
1959666049248165822465Twitter for iPhoneHere we have a 1949 1st generation vulpix. Enjoys sweat tea and Fox News. Cannot be phased. 5/10 https://t.co/4B7cOc1EDq5.010None2015-11-1600:24:50+00:00doggo9639https://pbs.twimg.com/media/CT5IQmsXIAAKY4A.jpg1miniature_pinscher0.560311Truerottweiler0.243682Truedoberman0.154629True
1960666044226329800704Twitter for iPhoneThis is a purebred Piers Morgan. Loves to Netflix and chill. Always looks like he forgot to unplug the iron. 6/10 https://t.co/DWnyCjf2mx6.010None2015-11-1600:04:52+00:00doggo265124https://pbs.twimg.com/media/CT5Dr8HUEAA-lEu.jpg1rhodesian_ridgeback0.408143Trueredbone0.360687Trueminiature_pinscher0.222752True
1961666033412701032449Twitter for iPhoneHere is a very happy pup. Big fan of well-maintained decks. Just look at that tongue. 9/10 would cuddle af https://t.co/y671yMhoiR9.010None2015-11-1523:21:54+00:00doggo10939https://pbs.twimg.com/media/CT4521TWwAEvMyu.jpg1german_shepherd0.596461Truemalinois0.138584Truebloodhound0.116197True
1962666029285002620928Twitter for iPhoneThis is a western brown Mitsubishi terrier. Upset about leaf. Actually 2 dogs here. 7/10 would walk the shit out of https://t.co/r7mOb2m0UI7.010None2015-11-1523:05:30+00:00doggo11941https://pbs.twimg.com/media/CT42GRgUYAA5iDo.jpg1redbone0.506826Trueminiature_pinscher0.074192Truerhodesian_ridgeback0.072010True
1963666020888022790149Twitter for iPhoneHere we have a Japanese Irish Setter. Lost eye in Vietnam (?). Big fan of relaxing on stair. 8/10 would pet https://t.co/BLDqew2Ijj8.010None2015-11-1522:32:08+00:00doggo2354448https://pbs.twimg.com/media/CT4udn0WwAA0aMy.jpg1welsh_springer_spaniel0.465074Truecollie0.156665Trueshetland_sheepdog0.061428True